Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading...Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.展开更多
Based on the log-linear virtual age process, an imperfect preventive maintenance policy for numerical control(NC)machine tools with random maintenance quality is proposed. The proposed model is a combination of the Ki...Based on the log-linear virtual age process, an imperfect preventive maintenance policy for numerical control(NC)machine tools with random maintenance quality is proposed. The proposed model is a combination of the Kijima type virtual age model and the failure intensity adjustment model. Maintenance intervals of the proposed hybrid model are derived when the failure intensity increase factor and the restoration factor are both random variables with uniform distribution. The optimal maintenance policy in infinite time horizon is presented. A numerical example is given when the failures of NC machine tools are described by the log-linear process. Finally, a discussion is presented to show how the optimal results depend on the different cost parameters.展开更多
A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect main...A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. Furthermore, the explicit expressions for the long-run average cost and availability per unit time of the system are evaluated, an optimal policy （ε^＊） could be determined numeri- cally or analytically according to the optimization model. At last, a numerical example for a degrading system modeled by a gamma process is presented to demonstrate the use of this policy in practical applications.展开更多
An optimal replacement model for gamma deteriorating systems is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reli...An optimal replacement model for gamma deteriorating systems is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. A maintenance policy （N） is applied by which the system will be repaired whenever it experiences Nth preventive maintenance （PM）, and an optimal policy （N＊） could be determined numerically or analytically for minimizing the long-run average cost per unit time. Finally, a numerical example is presented to demonstrate the use of this policy.展开更多
This paper presents a joint optimization policy of preventive maintenance(PM)and spare ordering for single-unit systems,which deteriorate subject to the delay-time concept with three deterioration stages.PM activities...This paper presents a joint optimization policy of preventive maintenance(PM)and spare ordering for single-unit systems,which deteriorate subject to the delay-time concept with three deterioration stages.PM activities that combine a non-periodic inspection scheme with age-replacement are implemented.When the system is detected to be in the minor defective stage by an inspection for the first time,place an order and shorten the inspection interval.If the system has deteriorated to a severe defective stage,it is either repaired imperfectly or replaced by a new spare.However,an immediate replacement is required once the system fails,the maximal number of imperfect maintenance(IPM)is satisfied or its age reaches to a pre-specified threshold.In consideration of the spare’s availability as needed,there are three types of decisions,i.e.,an immediate or a delayed replacement by a regular ordered spare,an immediate replacement by an expedited ordered spare with a relative higher cost.Then,some mutually independent and exclusive renewal events at the end of a renewal cycle are discussed,and the optimization model of such a joint policy is further developed by minimizing the long-run expected cost rate to find the optimal inspection and age-replacement intervals,and the maximum number of IPM.A Monte-Carlo based integration method is also designed to solve the proposed model.Finally,a numerical example is given to illustrate the proposed joint optimization policy and the performance of the Monte-Carlo based integration method.展开更多
An effective maintenance policy optimization model can reduce maintenance cost and system operation risk. For mission-oriented systems, the degradation process changes dynamically and is monotonous and irreversible. M...An effective maintenance policy optimization model can reduce maintenance cost and system operation risk. For mission-oriented systems, the degradation process changes dynamically and is monotonous and irreversible. Meanwhile, the risk of early failure is high. Therefore, this paper proposes a dynamic condition-based maintenance(CBM) optimization model for mission-oriented system based on inverse Gaussian(IG) degradation process. Firstly, the IG process with random drift coefficient is used to describe the degradation process and the relevant probability distributions are obtained. Secondly, the dynamic preventive maintenance threshold(DPMT) function is used to control the early failure risk of the mission-oriented system, and the influence of imperfect preventive maintenance(PM)on the degradation amount and degradation rate is analysed comprehensively. Thirdly, according to the mission availability requirement, the probability formulas of different types of renewal policies are obtained, and the CBM optimization model is constructed. Finally, a numerical example is presented to verify the proposed model. The comparison with the fixed PM threshold model and the sensitivity analysis show the effectiveness and application value of the optimization model.展开更多
基金supported by the National Natural Science Foundation of China(61873122)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.
基金Project(51465034)supported by the National Natural Science Foundation of China
文摘Based on the log-linear virtual age process, an imperfect preventive maintenance policy for numerical control(NC)machine tools with random maintenance quality is proposed. The proposed model is a combination of the Kijima type virtual age model and the failure intensity adjustment model. Maintenance intervals of the proposed hybrid model are derived when the failure intensity increase factor and the restoration factor are both random variables with uniform distribution. The optimal maintenance policy in infinite time horizon is presented. A numerical example is given when the failures of NC machine tools are described by the log-linear process. Finally, a discussion is presented to show how the optimal results depend on the different cost parameters.
基金supported by the National watural Science Foundation of China (60904002)
文摘A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. Furthermore, the explicit expressions for the long-run average cost and availability per unit time of the system are evaluated, an optimal policy （ε^＊） could be determined numeri- cally or analytically according to the optimization model. At last, a numerical example for a degrading system modeled by a gamma process is presented to demonstrate the use of this policy in practical applications.
基金supported by the National Natural Science Foundation of China (60904002)
文摘An optimal replacement model for gamma deteriorating systems is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. A maintenance policy （N） is applied by which the system will be repaired whenever it experiences Nth preventive maintenance （PM）, and an optimal policy （N＊） could be determined numerically or analytically for minimizing the long-run average cost per unit time. Finally, a numerical example is presented to demonstrate the use of this policy.
基金supported by the Naitonal Natural Science Foundation of China(71701038)China Ministry of Education Humanities and Social Sciences Research Youth Fund Project(16YJC630174)+2 种基金the Natural Science Foundation of Hebei Province(G2019501074)the Fundamental Research Funds for the Central Universities(N2123019)the Postgraduate Funding Project of PLA(JY2020B085).
文摘This paper presents a joint optimization policy of preventive maintenance(PM)and spare ordering for single-unit systems,which deteriorate subject to the delay-time concept with three deterioration stages.PM activities that combine a non-periodic inspection scheme with age-replacement are implemented.When the system is detected to be in the minor defective stage by an inspection for the first time,place an order and shorten the inspection interval.If the system has deteriorated to a severe defective stage,it is either repaired imperfectly or replaced by a new spare.However,an immediate replacement is required once the system fails,the maximal number of imperfect maintenance(IPM)is satisfied or its age reaches to a pre-specified threshold.In consideration of the spare’s availability as needed,there are three types of decisions,i.e.,an immediate or a delayed replacement by a regular ordered spare,an immediate replacement by an expedited ordered spare with a relative higher cost.Then,some mutually independent and exclusive renewal events at the end of a renewal cycle are discussed,and the optimization model of such a joint policy is further developed by minimizing the long-run expected cost rate to find the optimal inspection and age-replacement intervals,and the maximum number of IPM.A Monte-Carlo based integration method is also designed to solve the proposed model.Finally,a numerical example is given to illustrate the proposed joint optimization policy and the performance of the Monte-Carlo based integration method.
基金supported by the National Natural Science Foundation of China (71901216)。
文摘An effective maintenance policy optimization model can reduce maintenance cost and system operation risk. For mission-oriented systems, the degradation process changes dynamically and is monotonous and irreversible. Meanwhile, the risk of early failure is high. Therefore, this paper proposes a dynamic condition-based maintenance(CBM) optimization model for mission-oriented system based on inverse Gaussian(IG) degradation process. Firstly, the IG process with random drift coefficient is used to describe the degradation process and the relevant probability distributions are obtained. Secondly, the dynamic preventive maintenance threshold(DPMT) function is used to control the early failure risk of the mission-oriented system, and the influence of imperfect preventive maintenance(PM)on the degradation amount and degradation rate is analysed comprehensively. Thirdly, according to the mission availability requirement, the probability formulas of different types of renewal policies are obtained, and the CBM optimization model is constructed. Finally, a numerical example is presented to verify the proposed model. The comparison with the fixed PM threshold model and the sensitivity analysis show the effectiveness and application value of the optimization model.
